Abstract: An image processing apparatus determines the attribute of a pixel block, which is composed of a prescribed number of pixels extracted from image data, and the attribute of an area in which each pixel of the pixel block belongs. Then, based upon the determined attribute of the image block and the determined attribute of the area in which each pixel belongs, the apparatus subjects the image data to processing, pixel by pixel.

Abstract: A method for interpolation includes receiving an input image having a plurality of pixels. The edge direction proximate a first pixel of the input image is estimated using a first technique from a plurality of discrete potential directions. An edge direction is selected based upon the estimating the edge direction proximate the first pixel of the input image using a second technique. The pixels proximate the first pixel are interpolated based upon the selected edge direction. The pixels proximate the first pixel are interpolated based upon another technique. An output image is determined.

Abstract: Some of the embodiments of the present disclosure provide a method comprising selecting a pixel window of image data, the pixel window including a target pixel, determining a stability of the pixel window, formulating a look up table address based at least in part on the determined stability, obtaining one or more image enhancement values from a look up table based at least in part on the formulated look up table address, and processing the target pixel based at least in part on the obtained one or more image enhancement values. Other embodiments are also described and claimed.

Abstract: An image search method may include: determining a quadrant of a predicted motion vector; calculating a tilt value of a first reference frame and a tilt value of a second reference frame using the predicted motion vector; deciding a search area for uneven hexagon search in response to the quadrant of the predicted motion vector and the calculated tilt values; performing the uneven hexagon search with respect to the decided search area; and/or comparing a result of the performed uneven hexagon search with a threshold value to determine termination of the uneven hexagon search. The second reference frame is earlier-in-time relative to the first reference frame.

Abstract: Implementations feature scannable form techniques and systems. Some aspects feature an apparatus that includes a pen-camera device, an electronic clipboard to store the pen-camera device, and a docking station for the clipboard. The clipboard includes a retention clip to hold a form on a substantially planar surface, and a pen-camera storage compartment to store the pen-camera device. The clipboard includes a power supply interface for charging the pen-camera device, a communication interface to transmit image and location data from the pen-camera device, and electrical interfaces for the clipboard docking station. The pen-camera device can mark response data on the form, optically scan response data and location data on the form, and associate time-stamped information for the marked responses on the form for error checking and fraud detection. The scannable form can include an area for encoded information that identifies a location and arrangement of a position-coding pattern on the form.

Abstract: An image recognition device of the invention includes an image reading means for reading image information from a manuscript, discriminating a specific image in which a surrounded image is surrounded by a surrounding image from the image information. The image recognition device includes a first determination means for determining whether the surrounding image is included in the image information or not and a second determination means for determining whether there is the specific image in the image information or not by extracting n×n images to be processed by dividing an extraction region positioned at the center of the surrounding image into n×n regions (“n” is an odd-number of three or more) when the first determination means determines that the surrounding image is included in the image information, then, by checking respective images to be processed with a specific image template.

Abstract: Disclosed herein is a method of estimating a geometrical relationship between a first image (101) and a second image (102), wherein the second image (102) includes a noise component. The method determines a location and size of each one of a plurality of image patches (201), based on the noise component included in the second image (102) and correlation information derived from the first image (101). The method then identifies a plurality of first image areas in the first image and a corresponding plurality of second image areas in the second image, based on the location and size of each one of the plurality of image patches. Each first image area of the first image (101) corresponds to a related second image area of the second image (102).

Abstract: Disclosed are a system and a method extensible for performing, in real-time, stereo snatching for calculating depth images with a result of searching for points of similarity by using images taken with two cameras. The system includes a coordinate creating module, a census transform module, a delay XOR calculation module, a stereo matching module, and a control module. Accordingly, by using the system extensible for performing stereo matching, depth information of corrected images can be acquired in real-time without using computer systems or software programs for special purposes. Furthermore, since the system extensible for performing stereo matching can be simply realized by hardware, the system and the method of the present invention can be easily applied to actual intellectual-type robots, industrial settings, etc.

Abstract: A graphics processing apparatus is provided with rendering circuitry which separately renders different areas of a frame of pixel values. Monitoring circuitry coupled to the rendering circuitry captures for each area rendered one or more parameters and stores these parameters to a parameter memory. A performance frame can be generated from the captured and stored parameters with performance-representing pixel values for each area within the performance frame corresponding to an area within the image frame and having a visual characteristic selected in dependence upon the performance parameter which was captured. The visual characteristic may be a grey-scale value, a pixel intensity or a pixel color.

Abstract: Systems and methods for detecting a border region in an image. A blank border in a video picture is determined by summing luminance or other pixel measures in a direction parallel to the border and looking for the maximum gradient of those summed measures in a direction perpendicular to the border. Sensitivity can be enhanced by increasing (relative to other pixels) the gain of pixels around the present pixel value of the border. The location of the maximum gradient may be weighted by other measures before a decision on border location is taken.

Abstract: Frontal face images are classified into four categories such as Asian, Caucasian, African and others. A new representation of face appearance, named BITF (Block Intensity and Texture Feature), is employed as the discrimination feature. An ensemble of three component classifiers, each trained with a different number of BITF features as inputs, is designed to achieve a reliable classification. Further reliability is obtained by taking into consideration other secondary features to boost the classification performance.

Abstract: Image processing method that includes the steps of considering each image point as a node of an artificial neural network, and of processing the image as function of values of the nodes and of connections of each image point undergoing processing with neighboring image points, the image points of the processed image being obtained by iterative evolution steps of parameters defining the appearance as evolution steps of the value of nodes or by iterative evolution steps of values of the set of connections or by a combination of the evolutions, wherein the processing occurs by evolution iterative steps that are functions of connections of neighboring image points with the image point under examination, each of the neighboring image points being further considered as neighboring one or more or all adjacent image points, the functions providing immediate feedback contributions for determining appearance values of all other image points.

Abstract: A method of estimating position and orientation of a vehicle using image data is provided. The method includes capturing an image of a region external to the vehicle using a camera mounted to the vehicle, and identifying in the image a set of feature points of the region. The method further includes subsequently capturing another image of the region from a different orientation of the camera, and identifying in the image the same set of feature points. A pose estimation of the vehicle is generated based upon the identified set of feature points and corresponding to the region. Each of the steps are repeated at with respect to a different region at least once so as to generate at least one succeeding pose estimation of the vehicle. The pose estimations are then propagated over a time interval by chaining the pose estimation and each succeeding pose estimation one with another according to a sequence in which each was generated.

Abstract: An electronic visual aid is provided that includes an evaluating unit, which is supplied with a recording of an information carrier on which information standing out visibly from the background is displayed. The evaluating unit determines a brightness distribution of the recording and derives from the brightness distribution a brightness threshold value lying in the transition zone between a zone of the brightness distribution associated with the background and a zone of the brightness distribution associated with the information. The visual aid also includes an image processing unit which generates from the recording a binary image having only two different, predetermined brightness values, by respectively assigning to the pixels of the binary image the first of the two brightness values when the brightness of the corresponding pixel of the recording is below the brightness threshold value, and otherwise assigning the second brightness value.

Abstract: An extraction-pattern storing unit stores therein information related to a plurality of different extraction patterns for extracting a predetermined number of pixels from pixels surrounding a pixel that is a target for detecting a face part image. A face-part-image detecting unit extracts a pixel using the different extraction patterns stored in the extraction-pattern storing unit, and detects the face part image included in an image using a feature amount of an extracted pixel. A face-image detecting unit detects a face image from the image based on the face part image detected by the face-part-image detecting unit.

Abstract: A controller for scaling an input image is provided. The controller selects a pixel neighborhood that includes a plurality of pixels neighboring a pixel. The controller compares at least part of the pixel neighborhood to a pattern. If the pattern is present in the pixel neighborhood, the controller applies a scaling algorithm to at least a portion of the pixel neighborhood in order to obtain a scaled image. The controller also selects another pixel neighborhood that includes a plurality of pixels neighboring a pixel in the scaled image, and compares at least part of the another pixel neighborhood to another pixel pattern. If the another pixel pattern is present in the another pixel neighborhood, the controller applies a correction algorithm to at least a portion of the another pixel neighborhood in order to obtain a processed scaled image.

Abstract: There is provided an image processing apparatus. The image processing apparatus includes: an obtaining unit configured to capture an image; a specifying unit configured to specify at least one pixel on an edge of the image; a tracking unit configured to track pixels that are similar to the at least one pixel, among peripheral pixels around the at least one pixel; and an estimating unit configured to estimate, as a region of interest, a region other than a region consisting of the pixels tracked by the tracking unit.

Abstract: A method is presented for processing an image of a two-dimensional (2D) matrix symbol having a plurality of data modules and a discontinuous finder pattern, each distorted by “donut effects”. A resulting processed image contains an image of the 2D matrix symbol having a continuous finder pattern suitable for conventional 2D matrix symbol locating techniques, and having a plurality of data modules, each data module having a center more truly representative of intended data, and suitable for conventional 2D matrix symbol sampling and decoding. The method includes sharpening the distorted image of the 2D matrix symbol to increase a difference between low frequency and high frequency image feature magnitudes, thereby providing a sharpened image, and smoothing the sharpened image using a moving window over the sharpened image so as to provide a smoothed image, the moving window and a module of the 2D matrix code being of substantially similar size.

Abstract: An image noise detection method is disclosed. The image noise detection method includes the following steps: obtaining a spatial information of an image; obtaining a temporal information of the image; and determining a spatial noise or a temporal noise of the image according to both the spatial information, and the temporal information.

Abstract: A method of filtering and a degraining filter employ lowest edge activity (LEA) to assign a pixel value in a filtered image. A method of filtering includes selecting a set of pixels that includes a central pixel and pixels surrounding the central pixel from a digital image. The set has a plurality of subsets of pixels where at least one subset includes the central pixel. The method of filtering further includes assigning a value of a corresponding central pixel in a filtered image. The assigned value is a mean value of pixels in an identified subset of the plurality having the LEA. A degraining filter includes a processor, a memory and a computer program having instruction that implement selecting the set, identifying the subset with LEA and assigning the value.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes thresholding a window of pixels established in the contone domain to generate a binary window of image data, and then determining characteristics associated with on pixels or runs of the binary data. The characteristics (start and end locations, length of on runs) are then thresholded. The processing in the contone and binary domain are used to determine if a thin line exists in the window of image data. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: A system, method and computer program product for defect detection, the method includes: (i) retrieving a second pixel of a second image that corresponds to a tested pixel of a first image of the object; wherein the first and second images were obtained using different acquisition methods; (ii) searching a third pixel of the second image such that a neighborhood of the second pixel is similar to a neighborhood of the third pixel; (iii) retrieving a fourth pixel of the first image that corresponds to the third pixel; and (iv) comparing between the tested pixel and the fourth pixel.

Abstract: An object detecting apparatus capable of suppressing an increase of processing loads with high accuracy and a learning apparatus for the same are provided. An object detecting apparatus includes an image window extracting portion (210) for extracting an image window as a partial area of an image in plural from an input image, and a network identifier (590) for detecting a presence of an object from extracted image windows respectively by using a node network in which nodes each having an identifier for identifying the object stored in a storing portion (502) are connected as a network.

Abstract: Disclosed herein is a method for detecting thin lines in image data. The method is performed by a processor to process contone image data. The processing includes thresholding a window of pixels using a first set of thresholds established in the contone domain, and then counting and thresholding the binary pixels using a second set of thresholds. The processing in the contone and binary domain are used to determine if a thin line exists and if a pixel of interest in the window is an edge pixel that is part of a thin line. The disclosed method produces better quality output images and reduces the addition of false lines in an image.

Abstract: A gesture spotting detection method and apparatus employ a shoulder-line algorithm. The shoulder-line detecting method recognizes a GSD calling gesture that occurs in a shoulder-line, head or higher part in a remote distance or a short distance, although a user does not have a fixed posture. In the method, an image of people is received, and skin information of a person in the image is detected to detect a face area. Then, the cloth color information of the person is modeled from the inputted image to detect a cloth area. An external space is defined from the image based on the body space area, and an edge is extracted from the image based on the body space and the external space. Then, shoulder-line information is acquired based on an energy function obtained based on the body space, the external space, and the edge.

Abstract: In a system for detecting a target object, a similarity determining unit sets a block in a picked-up image, and compares a part of the picked-up image contained in the block with a pattern image data while changes a location of the block in the picked-up image to determine a similarity of each part of the picked-up image contained in a corresponding one of the different-located blocks with respect to the pattern image data. A specifying unit extracts some different-located blocks from all of the different-located blocks. The determined similarity of the part of the picked-up image contained in each of some different-located blocks is equal to or greater than a predetermined threshold similarity. The specifying unit specifies, in the picked-up image, a target area based on a frequency distribution of some different-located blocks therein.

Abstract: A camera auto-focuses using computed blur differences between images of a three-dimensional scene. The camera computes the blur difference between two images of the scene acquired at two different picture numbers. The camera uses the computed blur difference to predict a third picture number, where the camera uses the third picture number to auto-focus a camera lens on the scene.

Abstract: What is disclosed is a novel system and method for minimizing dot visibility in color marking devices capable of dot-on-dot printing. The present method achieves minimum dot visibility for a given dispersed-dot screen by performing a CMYK to CMYKRGB conversion which uses less visible dots as much as possible before more visible dots are introduced. The output color dot coverages are calculated sequentially to minimize the coverage of more visible dots in a decreasing order of brightness. Resulting images have noticeably reduced halftone graininess, particularly in the mid to darker tone areas. The present method is also computationally efficient.

Abstract: A digital image-processing device with a Bayer sensor and an image memory is provided in which the image data of the sensor is written into an image memory, and from this image memory, image data in the Bayer format with a length L and a width B is written continuously into a data buffer, and in which the sample values are combined by means of a computational device with the help of adders, in each case symmetrically to a central point of one or more (2n+1)×(2n+1) neighborhoods, and one or more (n+1)×(n+1) matrices are derived by means of the computational device, and from this (n+1)×(n+1) matrix or these matrices, with the help of additional adders, at least one n×n matrix is formed, and a first color component is in each case calculated from this by means of an adder network.

Abstract: The image feature extraction method of the present invention includes: the step of performing k2 dividing process at least once on a given image so as to convert the given image into a multi-divided image, where the k2 dividing process comprises the steps of: a) creating matrix T based on image matrix X; b) computing singular values of the matrix T; c) determining whether or not minj|?j??j?1|>?; d) if the result of the determination in the step c) is “No”, returning to the step c) subsequent to computing the singular values of the enlarged matrix T?; e) if the result of the determination in the step c) is “Yes”, obtaining U which satisfies T=USVT; f) obtaining matrix T1=UTT; and g) creating image matrix X1 based on matrix T1.

Abstract: A method and apparatus for reducing false color artifacts in digital images. Aperture correction and color saturation values are determined for a portion of an image surrounding a subject pixel. A color attenuation value is determined based at least in part on the aperture correction and color saturation values. A color value of the subject pixel is adjusted by an amount based at least in part on the color attenuation value. In one exemplary embodiment, the method and apparatus operate in the YUV color space and adjust U and V values of the subject pixel proportionally to the color attenuation value.

Abstract: Computer-implemented image processing methods and apparatuses are presented for automatically selecting regions of interest within an image represented by pixel intensity values. A first pixel box is employed in progressively scanning and evaluating the image. If pixels within the first pixel box have pixel-intensity-related characteristics exceeding respective defined thresholds, then those pixels are identified as an area of interest and a second pixel box is employed in progressively scanning and evaluating the selected area of interest to identify regions of interest. Each area of interest is larger than a region of interest, and the second pixel box is smaller than the first. Regions of interest within the image are identified if one or more pixel-intensity-related characteristics of pixels within the second pixel box exceeds a second defined threshold, wherein the second threshold is greater than the first. Once selected, identifying information for the regions of interest is stored or output.

Abstract: [PROBLEMS] To provide a feature extracting method for quickly extracting a feature while preventing lowering of the identification performance of the kernel judgment analysis, a feature extracting system, and a feature extracting program. [MEANS FOR SOLVING PROBLEMS] Judgment feature extracting device (104) computes an interclass covariance matrix SB and an intraclass covariance matrix SW about a learning face image prepared in advance, determines optimum vectors ?, ? which maximizes the ratio of the interclass covariance to the intraclass covariance, derives a conversion formula for converting an inputted frequency feature vector x into a frequency feature vector y in a judgment space, and extracts judgment features of a face image for record and a face image for check by using a restructured conversion formula. Similarity computing device (105) computes the similarity by comparing the judgment features.

Abstract: A scanning electron microscope comprises an image processing system for carrying out a pattern matching between a first image and a second image. The image processing system comprises: a paint-divided image generator for generating a paint divided image based on the first image; a gravity point distribution image generator for carrying out a smoothing process of the paint divided image and generating a gravity point distribution image; an edge line segment group generation unit for generating a group of edge line segments based on the second image; a matching score calculation unit for calculating a matching score based on the gravity point distribution image and the group of edge line segments; and a maximum score position detection unit for detecting a position where the matching score becomes the maximum.

Abstract: The present invention discloses a method for the detection of atypical vessels in digital cervical imagery. A pre-processing stage is applied to enhance the contrast of blood vessel features compared to the surrounding tissue. Next, a segmentation stage is applied to identify regions of interest for atypical vessels using texture and gradient information. Finally, a post-processing stage (1) identifies other clinically relevant features in the cervical imager, and removes these features from the region of interest; and (2) uses color, size, and shape information to further refine the region of interest to eliminate false positives and determine a final region of interest. This automated method of atypical vessel detection is especially useful for diagnostic purposes such as cervical cancer detection.

Abstract: A color conversion apparatus receives first image data including first red-green-blue color data in which the possible values of the red, green, and blue components extend beyond the range from 0% to 100%. The first color data are analyzed into first hue region data, the magnitudes of which are adjusted according to the brightness and/or saturation of the first color data to obtain second and third hue region data. The gamut of colors of the first image data is detected, and matrix coefficients are generated according to the detected gamut. The matrix coefficients are used to perform a matrix operation on the second and third hue region data to obtain second color data, thereby converting the first image data to second image data with conversion characteristics appropriate for the gamut of colors of the first image data.

Abstract: Low complexity (16 bit arithmetic) video compression has 8×8 block with transforms using 8×8 integer matrices and quantization with look up table scalar plus constant right shift for all quantization steps. Inverse quantization also a look up table scalar plus right shift dependent upon the quantization step and inverse transform using the 8×8 integer matrices.

Abstract: The present invention provides a method and module for preprocessing ultrasound imaging. The method comprises a calculation step for constructing a multivalue vector field and a smoothing step for smoothing the whole volume data. The method further comprises a judgement step and minification and magnification steps. The module includes a calculation unit, a smoothing unit, a judgement unit, a minification unit and a magnification unit. According to the method for preprocessing ultrasound imaging, speckle noise can be eliminated effectively by calculating a mean value of a plurality of nodes distributed over the surface, so as to implement the smoothing. Therefore, this method is capable of smoothing data without compromising details.

Abstract: Improved surface feature recognition in CT images is provided by extracting a triangulated mesh representation of the surface of interest. Shape operators are computed at each vertex of the mesh from finite differences of vertex normals. The shape operators at each vertex are smoothed according to an iterative weighted averaging procedure. Principal curvatures at each vertex are computed from the smoothed shape operators. Vertices are marked as maxima and/or minima according to the signs of the principal curvatures. Vertices marked as having the same feature type are clustered together by adjacency on the mesh to provide candidate patches. Feature scores are computed for each candidate patch and the scores are provided as output to a user or for further processing.

Abstract: An apparatus receives a base image and a reference image that are images picked up by two cameras provided on left and right. A weight coefficient determination portion determines a coefficient for cutting off a high-frequency region of combined phase spectrum of the base image and the reference image, based on an image pickup condition of the camera and texture information of the image in a window centered on a gaze point within the base image.

Abstract: A rectangular area containing sections corresponding to same weather information is set. If sections at four corners of the set area are sections corresponding to the same weather information, a numerical value “1” is set as a weighting score to the sections. If not so, a numerical value “0” is set to the sections. Sections to which no weighting score is allocated and which are adjacent to sections to which weighting scores have been allocated are successively selected from the outer edge side, and the maximum value of the weighting scores of the four sections adjacent to each selected section is set as a weighting score of the selected section. If the previously selected section is a section corresponding to the weather information, the numerical value “1” is added to the weighting score of the section. The section having the highest weighting score is selected as a specific section, and an icon is displayed on the specific section.

Abstract: A camera or other optical system is focused by generating a plurality of digital images each obtained with a different focus setting of the optical system. These images are analysed to generate for each image a score (S) by comparing first groups of pixels chosen from the image with second groups chosen from the image such that the pixels of each second group have same respective positional relationships with respect to one another as the pixels of the first group with which it is compared have to one another, the score (S) being a function of the number of matches obtained with said comparisons. The focus setting that gives the score corresponding to the largest number of matches is chosen.

Abstract: A system for identifying artifacts in an image. The system includes an input for receiving images from an imager, the images comprising a pixel of interest. The images can be generated by reflecting light off an object. The system further includes a processor coupled to the input for defining and using at least one contrast value of a second pixel associated with the pixel of interest to identify artifacts in the image.

Abstract: An apparatus and method for selectively outputting image frames are provided. The apparatus includes a main topic frame extractor which extracts a main topic frame, which expresses a main topic selected by a user, from continuous image frames; a composite image frame creator which extracts a key object to realize the main topic from the main topic frames, and estimates a background object with respect to the key object to create a composite image frame using the key object and the background object; a wide-angle image frame creator which creates a wide-angle image frame, which includes the composite image frame and an image frame having common information to the composite image frame, among the continuous image frames; an attractive region setting unit which sets an attractive region with respect to the wide-angle image frame; and an output unit which outputs the attractive region.

Abstract: What is disclosed is a novel system and method for encoding/decoding data in a cover contone image via halftone dot orientation modulation. Arrays of halftone threshold values are used to determine a desired orientation, e.g. 0/90°+/?45° for a given single data value of the original message to be embedded. Message data is embedded as a function of halftone dot orientation. Detection modeling of the print-scan process enables the determination of dot orientation from the image scan via statistically motivated image moments. A probabilistic model of the print-scan channel conditions received moments on input orientation. Density values of the received moments are used to determine dot orientation for each halftone cell. The embedded data is retrieved based on the determined orientations. The present method is applicable to areas of data embedding, document security, and the like.

Abstract: In an image-processing apparatus having a capability of performing region distinction processing and an image region discrimination processing method, a first region distinction unit uses a previously set threshold value for an image region distinction to perform a region distinction processing of a character and a non-character on image data read from an original document, an edge feature amount image and a character determination signal are obtained, a second region distinction unit makes a region distinction on the edge feature amount image based on the threshold value and generates and displays sub-region images obtained by dividing the edge feature amount image into plural parts, a character discrimination strength adjustment is performed on a display screen while each of the sub-region images is visually identified, the correction parameter is reflected in the edge feature amount image, and the region distinction processing is performed again.

Abstract: The invention provides a method and apparatus for performing correspondence estimation between pixels of a stereo image pair to obtain matching information for corresponding pixels in each image. To perform a match for a particular pixel in a first image firstly an adaptive curve is constructed about the pixel, being a sequence of connected pixels with similar intensity values to the pixel being matched. The adaptive curve thus constructed is then used as a matching element within the second image to find a matching pixel representative of the same 3D scene point in the second image to the particular pixel. By performing matching in this manner for every pixel in an image, accurate disparity maps can be obtained which are then used in a known image synthesis algorithm to produce novel images of a scene of improved quality.

Abstract: A system, method and computer program product for defect detection, the method includes: (i) retrieving a second pixel of a second image that corresponds to a tested pixel of a first image of the object; wherein the first and second images were obtained using different acquisition methods; (ii) searching a third pixel of the second image such that a neighborhood of the second pixel is similar to a neighborhood of the third pixel; (iii) retrieving a fourth pixel of the first image that corresponds to the third pixel; and (iv) comparing between the tested pixel and the fourth pixel.

Abstract: A method is presented for processing an image of a two-dimensional (2D) matrix symbol having a plurality of data modules and a discontinuous finder pattern, each distorted by “donut effects”. A resulting processed image contains an image of the 2D matrix symbol having a continuous finder pattern suitable for conventional 2D matrix symbol locating techniques, and having a plurality of data modules, each data module having a center more truly representative of intended data, and suitable for conventional 2D matrix symbol sampling and decoding. The method includes sharpening the distorted image of the 2D matrix symbol to increase a difference between low frequency and high frequency image feature magnitudes, thereby providing a sharpened image, and smoothing the sharpened image using a moving window over the sharpened image so as to provide a smoothed image, the moving window and a module of the 2D matrix code being of substantially similar size.

Abstract: A method for detecting a facial area on a color image includes (a) placing a search window on the color image, (b) determining if a center pixel of the search window is a skin color pixel, indicating that the search window is a possible facial area candidate, (c) applying a 3-rectangle filter to the search window to determine if the search window is a possible facial area candidate, (d) applying a 4-rectangle filter to the search window to determine if the search window is a possible facial area candidate, (e) if steps (b), (c), (d) all determine that the search window is a possible facial area candidate, applying an AdaBoost filter to the search window to determine if the search window is a facial area candidate, and (f) if step (e) determines that the search window is a facial area candidate, saving the location of the search window.